NIPS 1988: Denver, CO, USA

David S. Touretzky (Ed.): Advances in Neural Information Processing Systems 1, [NIPS Conference, Denver, Colorado, USA, 1988]. Morgan Kaufmann 1989, ISBN 1-55860-015-9 BibTeX

@proceedings{DBLP:conf/nips/1988,
  editor    = {David S. Touretzky},
  title     = {Advances in Neural Information Processing Systems 1, [NIPS Conference,
               Denver, Colorado, USA, 1988]},
  booktitle = {NIPS},
  publisher = {Morgan Kaufmann},
  year      = {1989},
  isbn      = {1-55860-015-9},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Part 1: Learning and Generalization

Mark A. Gluck, M. Pavel, Van Henkle:
Constraints on Adaptive Networks for Modeling Human Generalization. 2-10
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Terence D. Sanger:
An Optimality Principle for Unsupervised Learning. 11-19
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David H. Ackley:
Associative Learning via Inhibitory Search. 20-28
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John E. Moody:
Fast Learning in Multi-Resolution Hierarchies. 29-39
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Alan H. Kramer, Alberto L. Sangiovanni-Vincentelli:
Efficient Parallel Learning Algorithms for Neural Networks. 40-48
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Lawrence Davis:
Mapping Classifier Systems Into Neural Networks. 49-56
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Manoel Fernando Tenorio, Wei-Tsih Lee:
Self Organizing Neural Networks for the Identification Problem. 57-64
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Pierre Baldi:
Linear Learning: Landscapes and Algorithms. 65-72
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Tal Grossman, Ronny Meir, Eytan Domany:
Learning by Choice of Internal Representations. 73-80
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Eric B. Baum, David Haussler:
What Size Net Gives Valid Generalization? 81-90
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Griff L. Bilbro, Reinhold Mann, Thomas K. Miller, Wesley E. Snyder, David E. van den Bout, Mark White:
Optimization by Mean Field Annealing. 91-98
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Gerald Tesauro:
Connectionist Learning of Expert Preferences by Comparison Training. 99-106
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Michael Mozer, Paul Smolensky:
Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment. 107-115
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Eyal Yair, Allen Gersho:
The Boltzmann Perceptron Network: A Multi-Layered Feed-Forward Network Equivalent to the Boltzmann Machine. 116-123
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Richard Lippmann, Paul Beckman:
Adaptive Neural Net Preprocessing for Signal Detection in Non-Gaussian Noise. 124-132
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Sharad Singhal, Lance Wu:
Training Multilayer Perceptrons with the Extende Kalman Algorithm. 133-140
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Yann LeCun, Conrad C. Galland, Geoffrey E. Hinton:
GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection. 141-148
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Patrice Simard, Mary B. Ottaway, Dana H. Ballard:
Fixed Point Analysis for Recurrent Networks. 149-159
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Subutai Ahmad, Gerald Tesauro:
Scaling and Generalization in Neural Networks: A Case Study. 160-168
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Raoul Tawel:
Does the Neuron "Learn" Like the Synapse? 169-176
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Stephen Jose Hanson, Lorien Y. Pratt:
Comparing Biases for Minimal Network Construction with Back-Propagation. 177-185
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Ralph Linsker:
An Application of the Principle of Maximum Information Preservation to Linear Systems. 186-194
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David B. Parker, Mark A. Gluck, Eric S. Reifsnider:
Learning with Temporal Derivatives in Pulse-Coded Neuronal Systems. 195-203
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Part 2: Application

Hong C. Leung, Victor Zue:
Applications of Error Back-Propagation to Phonetic Classification. 206-214
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Alex Waibel:
Consonant Recognition by Modular Construction of Large Phonemic Time-Delay Neural Networks. 215-223
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Yoshua Bengio, Régis Cardin, Renato de Mori, Piero Cosi:
Use of Multi-Layered Networks for Coding Speech with Phonetic Features. 224-231
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Mitsuo Komura, Akio Tanaka:
Speech Production Using A Neural Network with a Cooperative Learning Mechanism. 232-239
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Erich J. Smythe:
Temporal Representations in a Connectionist Speech System. 240-247
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Richard Fozzard, Gary Bradshaw, Louis Ceci:
A Connectionist Expert System that Actually Works. 248-255
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Rodney M. Goodman, John W. Miller, Padhraic Smyth:
An Information Theoretic Approach to Rule-Based Connectionist Expert Systems. 256-263
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Martine Naillon, Jean-Bernard Theeten:
Neural Approach for TV Image Compression Using a Hopfield Type Network. 264-271
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Bernd-Peter Paris, Geoffrey C. Orsak, Mahesh K. Varanasi, Behnaam Aazhang:
Neural Net Receivers in Multiple Access-Communications. 272-280
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Stanley C. Ahalt, F. D. Garber, I. Jouny, Ashok K. Krishnamurthy:
Performance of Synthetic Neural Network Classification of Noisy Radar Signals. 281-288
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Allen M. Waxman, Michael Seibert, Robert K. Cunningham, Jian Wu:
Neural Analog Diffusion-Enhancement Layer and Spatio-Temporal Grouping in Early Vision. 289-296
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Anya C. Hurlbert, Tomaso Poggio:
A Network for Image Segmentation Using Color. 297-304
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Dean Pomerleau:
ALVINN: An Autonomous Land Vehicle in a Neural Network. 305-313
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Phillip Alvelda, A. Miguel San Martin:
Neural Network Star Pattern Recognition for Spacecraft Attitude Determination and Control. 314-322
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John S. Denker, W. R. Gardner, Hans Peter Graf, Donnie Henderson, R. E. Howard, Wayne E. Hubbard, Lawrence D. Jackel, Henry S. Baird, Isabelle Guyon:
Neural Network Recognizer for Hand-Written Zip Code Digits. 323-331
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Yoshihiro Mori, Kazuhiko Yokosawa:
Neural Networks that Learn to Discriminate Similar Kanji Characters. 332-339
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Timothy S. Wilkinson, Dorothy A. Mighell, Joseph W. Goodman:
Backpropagation and Its Application to Handwritten Signature Verification. 340-347
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Bartlett W. Mel:
Further Explorations in Visually-Guided Reaching: Making MURPHY Smarter. 348-355
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Kenneth Y. Goldberg, Barak A. Pearlmutter:
Using Backpropagation with Temporal Windows to Learn the Dynamics of the CMU Direct-Drive Arm II. 356-363
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Part 3: Neurobiology

Clay Spence, John C. Pearson, J. J. Gelfand, R. M. Peterson, W. E. Sullivan:
Neuronal Maps for Sensory-Motor Control in the Barn Owl. 366-374
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Kenneth D. Miller, Joseph B. Keller, Michael P. Stryker:
Models of Ocular Dominance Column Formation: Analytical and Computational Results. 375-383
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Sylvie Ryckebusch, James M. Bower, Carver Mead:
Modeling Small Oscillating Biological Networks in Analog VLSI. 384-393
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Patric K. Stanton, Terrence J. Sejnowski:
Storing Covariance by the Associative Long-Term Potentation and Depression of Synaptic Strengths in the Hippocampus. 394-401
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Zhaoping Li, John J. Hopfield:
Modeling the Olfactory Bulb - Coupled Nonlinear Oscillators. 402-409
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Michael G. Paulin, Mark E. Nelson, James M. Bower:
Neural Control of Sensory Acquisition: The Vestibulo-Ocular Reflex. 410-418
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Daniel L. Alkon, Francis K. H. Quek, Thomas P. Vogl:
Computer Modeling of Associative Learning. 419-435
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Brian Rasnow, Christopher Assad, Mark E. Nelson, James M. Bower:
Simulation and Measurement of the Electric Fields Generated by Weakly Electric Fish. 436-443
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Jun Zhang, John P. Miller:
A Model for Resolution Enhancement (Hyperacuity) in Sensory Representation. 444-450
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Shigeru Tanaka:
Theory of Self-Organization of Cortical Maps. 451-458
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Bill Baird:
A Bifurcation Theory Approach to the Programming of Periodic Attractors in Network Models of Olfactory Cortex. 459-467
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Martin I. Sereno:
Learning the Solution to the Aperture Problem for Pattern Motion with a Hebb Rule. 468-476
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Norberto M. Grzywacz, Franklin R. Amthor:
A Computationally Robust Anatomical Model for Retinal Directional Selectivity. 477-484
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Matthew A. Wilson, Upinder S. Bhalla, John D. Uhley, James M. Bower:
GENESIS: A System for Simulating Neural Networks. 485-492
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Part 4: Structured Networks

Avrim Blum, Ronald L. Rivest:
Training a 3-Node Neural Network is NP-Complete. 494-501
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Hervé Bourlard, Christian Wellekens:
Links Between Markov Models and Multilayer Perceptrons. 502-510
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Moshe Kam, Roger Cheng:
Convergence and Pattern-Stabilization in the Boltzmann Machine. 511-518
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Yves Chauvin:
A Back-Propagation Algorithm with Optimal Use of Hidden Units. 519-526
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Jordan B. Pollack:
Implications of Recursive Distributed Representations. 527-536
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Eugene Santos Jr.:
A Massively Parallel Self-Tuning Context-Free Parser. 537-544
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Trent E. Lange, Michael G. Dyer:
Dynamic, Non-Local Role Bindings and Inferencing in a Localist Network for Natural Language Understanding. 545-552
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James A. Hendler:
Spreading Activation over Distributed Microfeatures. 553-559
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A. B. Kirillov, Galina Borisyuk, Roman Borisyuk, Ye. I. Kovalenko, V. I. Makarenko, V. A. Chulaevsky, V. I. Kryukov:
A Model of Neural Oscillator for a Unified Submodule. 560-567
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Charles M. Marcus, R. M. Westervelt:
Dynamics of Analog Neural Networks with Time Delay. 568-576
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Randall D. Beer, Hillel J. Chiel, Leon Sterling:
Heterogeneous Neural Networks for Adaptive Behavior in Dynamic Environments. 577-585
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David Rogers:
Statistical Prediction with Kanerva's Sparse Distributed Memory. 586-593
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Griff L. Bilbro, Wesley E. Snyder:
Range Image Restoration Using Mean Field Annealing. 594-601
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Jared Leinbach:
Automatic Local Annealing. 602-609
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V. I. Kryukov:
"Neurolocator", A Model of Attention. 610-617
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Eric Mjolsness, Gene Gindi, P. Anandan:
Neural Networks for Model Matching and Perceptual Organization. 618-625
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David S. Touretzky:
Analyzing the Energy Landscapes of Distributed Winner-Take-All Networks. 626-633
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E. Majani, Ruth Erlanson, Yaser S. Abu-Mostafa:
On the K-Winners-Take-All Network. 634-642
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David Servan-Schreiber, Axel Cleeremans, James L. McClelland:
Learning Subsequential Structure in Simple Recurrent Networks. 643-652
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C. L. Winter:
An Adaptive Network That Learns Sequences of Transitions. 653-660
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Part 5: Implementation

David Feld, Joe Eisenberg, Edwin Lewis:
A Passive Shared Element Analog Electrical Cochlea. 662-670
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Alister Hamilton, Alan F. Murray, Lionel Tarassenko:
Programmable Analog Pulse-Firing Neural Networks. 671-677
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Jack L. Meador, Clint S. Cole:
A Low-Power CMOS Circuit Which Emulates Temporal Electrical Properties of Neurons. 678-686
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John G. Harris:
An Analog VLSI Chip for Thin-Plate Surface Interpolation. 687-694
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Bahram Nabet, Robert B. Darling, Robert B. Pinter:
Analog Implementation of Shunting Neural Networks. 695-702
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John Lazzaro, Sylvie Ryckebusch, Misha Mahowald, Carver Mead:
Winner-Take-All Networks of O(N) Complexity. 703-711
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Paul Mueller, Jan Van der Spiegel, David Blackman, Timothy Chiu, Thomas Clare, Joseph Dao, Christopher Donham, Tzu-pu Hsieh, Marc Loinaz:
A Programmable Analog Neural Computer and Simulator. 712-719
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Tobi Delbrück, Carver Mead:
An Electronic Photoreceptor Sensitive to Small Changes in Intensity. 720-727
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Martin J. Johnson, Nigel M. Allinson, Kevin J. Moon:
Digital Realisation of Self-Organizing Maps. 728-738
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James R. Mann, Sheldon Gilbert:
An Analog Self-Organizing Neural Network Chip. 739-747
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Joshua Alspector, Bhusan Gupta, Robert B. Allen:
Performance of a Stochastic Learning Microchip. 748-760
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Daniel B. Schwartz, R. E. Howard, Wayne E. Hubbard:
Adaptive Neural Networks Using MOS Charge Storage. 761-768
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Allan Hartstein, R. H. Koch:
A Self-Learning Neural Network. 769-776
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M. R. Walker, S. Haghighi, A. Afghan, Larry A. Akers:
Training a Limited-Interconnect, Synthetic Neural IC. 777-784
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Andreas G. Andreou:
Electronic Receptors for Tactile/Haptic Sensing. 785-792
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Appendix: Summaries of Invited Talks

Valentino Braitenberg:
Neural Architecture. 794
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M. Konishi:
Song Learning in Birds. 795
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John S. Bridle:
Speech Recognition: Statistical and Neural Information Processing Approaches. 796-801
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John P. Miller:
Cricket Wind Detection. 802-807
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